This paper presents a novel approach to pedestrian classification which involves utilizing the synthesized virtual samples of a learned generative model to enhance the classificat...
In this paper we describe a new Bayesian estimation approach for simultaneous mapping and localization for pedestrians based on odometry with foot mounted inertial sensors. When s...
Patrick Robertson, Michael Angermann, Bernhard Kra...
Pedestrian detection from images is an important and yet challenging task. The conventional methods usually identify human figures using image features inside the local regions. In...
Detecting different categories of objects in image and video content is one of the fundamental tasks in computer vision research. The success of many applications such as visual s...
In this paper, we propose a method for extracting image features which utilizes 2 nd order statistics, i.e., spatial and orientational auto-correlations of local gradients. It enab...